Subset Principle: Learning, even at its start, takes place in a (simplified) subset of the real domain. For example, the setting for the loading dock game should represent an actual loading dock, so that players can easily map their in-game behavior to on-the-job performance. However, it must be a simplified version that omits unimportant details, so that players can focus on aspects of the simulation that are relevant to the learning objective—things like crosswalks and pedestrians.
Active, Critical Learning Principle: The learning environment must encourage active and critical, not passive, learning. In the loading dock example, this means players do not merely watch correct and incorrect examples of loading dock behavior, followed by a quiz—they actually think, act, experience consequences and pursue goals in a variable game environment.
Probing Principle: Learning is a cycle of probing the world (doing something); reflecting on this action and, on this basis, forming a hypothesis; re-probing the world to test the hypothesis; and then accepting or rethinking the hypothesis. For example, an effective loading dock game must present a functional environment in which players may choose from and evaluate many different actions. The goal is to find the right course of action via experimentation—making choices and experiencing the consequences.
Practice Principle: Learners get lots of practice in a context where the practice is not boring (i.e. in a virtual world that is compelling to learners on their own terms and where the learners experience ongoing success). For example, to encourage practice—and thus, development of good habits—the loading dock game must gradually increase the difficulty level of the in-game challenges. This keeps players engaged and encourages them to continually hone their skills.
